Systems and methods for dental practice planning and management

ABSTRACT

System and methods for the integration of dental practice management systems are disclosed herein. The systems and methods may generate models (including schedule models and financial models) from the data provided by a plurality of dental practices. These models can be used to quantitatively evaluate the efficiency and other operating characteristics of a particular dental practice, and can identify operational issues within the practice. Further, the systems and methods can evaluate metrics of the dental practice against goal metrics and/or standard metrics, and recommend and implement solutions based on the comparison.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is continuation of PCT Application No.PCT/US2018/012378, filed on Jan. 4, 2018 entitled “SYSTEM AND METHODSFOR DENTAL PRACTICE PLANNING AND MANAGEMENT,” which claims priority toU.S. provisional patent application No. 62/442,907, filed on Jan. 5,2017 entitled “SYSTEM AND METHODS FOR DENTAL PRACTICE PLANNING ANDMANAGEMENT,” both of which are incorporated by reference herein in theirentireties.

FIELD

The present disclosure relates to systems for resource management andanalysis of dental practices.

BACKGROUND

Dental practices typically utilize one or more software and/or hardwaresystems to manage various aspects of the practices. Billing, scheduling,and expense management, for example, are frequently managed usingcomputer-based solutions. However, utilizing multiple individual ordistinct systems for various aspects of dental practice management canbe inefficient and potentially expensive. A unified computer-basedsolution may provide increased efficiency and/or reduced cost.

Further, to improve efficiency, many dental practices seek professionaladvisement, such as from a dental management consultant. Consultants mayanalyze various aspects of a dental practice to determine areas ofpotential improvement. It may be beneficial for dental practices andconsultants to have access to data and data models of similar dentalpractices, which would allow for direct comparison of the performance ofa particular dental practice with the performance of similar practices.

SUMMARY

Systems, methods, and computer readable medium (collectively, the“system”) are disclosed for managing dental practices. The systems maygenerate financial and schedule data from a first user system, and afinancial model and a schedule model from data received from a pluralityof user systems utilized by dental practices having a sharedcharacteristic to the first user system. The systems may compare thefinancial data to the revenue model and the schedule data to theschedule model.

In various embodiments, the systems comprise an application server, aformatted database, and a data processing module. The systems mayfurther comprise a consultant user interface in communication with atleast one of the formatted database and the data processing module. Theconsultant user interface may determine which data is transmitted fromthe application server to the first user system.

The forgoing features and elements may be combined in variouscombinations without exclusivity, unless expressly indicated hereinotherwise. These features and elements as well as the operation of thedisclosed embodiments will become more apparent in light of thefollowing description and accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter of the present disclosure is particularly pointed outand distinctly claimed in the concluding portion of the specification. Amore complete understanding of the present disclosure, however, may beobtained by referring to the detailed description and claims whenconsidered in connection with the drawing figures, wherein like numeralsdenote like elements.

FIG. 1A illustrates a system for dental practice planning andmanagement, in accordance with various embodiments;

FIG. 1B illustrates another system for dental practice planning andmanagement, in accordance with various embodiments;

FIG. 1C illustrates yet another system for dental practice planning andmanagement, in accordance with various embodiments;

FIG. 2 illustrates a graphical user interface of a dashboard of a dentalintegration platform, in accordance with various embodiments;

FIG. 3 illustrates a flow chart for the operation of a treatmentapplication of the dental integration platform, in accordance withvarious embodiments;

FIG. 4 illustrates a flow chart for the operation of a softwareapplication of the dental integration platform for managing day-to-dayoperations, in accordance with various embodiments;

FIG. 5 illustrates a graphical user interface of the softwareapplication of FIG. 4, in accordance with various embodiments;

FIG. 6 illustrates another graphical user interface of the softwareapplication of FIG. 4, in accordance with various embodiments;

FIG. 7 illustrates a flow chart for the operation of a softwareapplication of the dental integration platform for monitoring andanalysis of accounts receivables and collections, in accordance withvarious embodiments;

FIG. 8 illustrates a graphical user interface of the softwareapplication of FIG. 7, in accordance with various embodiments;

FIG. 9 illustrates a method for operating a dental integration platformin accordance with various embodiments;

FIG. 10 illustrates a method for improving operations of a dentalpractice in accordance with various embodiments;

FIG. 11 illustrates a graphical display of a user interface inaccordance with various embodiments;

FIG. 12 illustrates another graphical display of a user interface inaccordance with various embodiments;

FIG. 13 illustrates a process for managing content relevant to a dentalpractice, in accordance with various embodiments;

FIG. 14 illustrates a sub-process for tagging content relevant to adental practice, in accordance with various embodiments; and

FIG. 15 illustrates a process for providing relevant tagged content to adental practice, in accordance with various embodiments.

DETAILED DESCRIPTION

The detailed description of various embodiments herein makes referenceto the accompanying drawings and pictures, which show variousembodiments by way of illustration. While these various embodiments aredescribed in sufficient detail to enable those skilled in the art topractice the disclosure, it should be understood that other embodimentsmay be realized and that logical and mechanical changes may be madewithout departing from the spirit and scope of the disclosure. Thus, thedetailed description herein is presented for purposes of illustrationonly and not of limitation. For example, the steps recited in any of themethod or process descriptions may be executed in any order and are notlimited to the order presented. Moreover, any of the functions or stepsmay be outsourced to or performed by one or more third parties.Furthermore, any reference to singular includes plural embodiments, andany reference to more than one component may include a singularembodiment.

The present disclosure provides systems, methods, and computer programproducts for managing dental practices, although the systems describedherein are envisioned as applying to medical practices, legal practices,and any other professional practices. With reference to FIGS. 1A and 1B,systems 100A and 100B, respectively, are shown, in accordance withvarious embodiments. Systems 100A and 100B may comprise a first usersystem 102 running a native application and/or a web browser. First usersystem 102 may comprise any system or device capable of receiving,storing, manipulating, and/or displaying electronic data. For example,first user system 102 may take the form of a computer or processor, or aset of computers/processors, although other types of computing units orsystems may be used, including laptops, notebooks, hand held computers,personal digital assistants, cellular phones, smart phones (e.g.,iPhone®, BlackBerry®, Android®, etc.), tablets, wearables (e.g., smartwatches and smart glasses), or any other device capable of receiving anddisplaying electronic data.

In various embodiments, first user system 102 is utilized by one or moreemployees of a dental practice, for the purposes of entering datarelated to the operation of the dental practice. For example, first usersystem 102 can comprise a computer system into which employees of thedental practice input data such as patient data, scheduling data,billing data, financial data (including, among others, revenue dataand/or expense data), and any other data relevant to the operation ofthe dental practice. First user system 102 may comprise, for example,one or more software applications that facilitate the entry and storageof relevant data. Such software applications can comprise, for example,billing software, patient management software, accounting software, andscheduling software, among others.

First user system 102 can comprise, for example, a dental practicemanagement system (“DPMS”) which stores data input by various employeesof the dental practice in a particular and/or proprietary format. Inthat regard, each DPMS may have a different schema and/or structure inwhich data is stored. For example, first user system 102 may include aDPMS that stores relevant data in a relational database within firstuser system 102 comprising various tables related by keys. The DPMS offirst user system 102 can be local (i.e., a program stored within andexecuted by a local computer), cloud-based, or any other configurationthat allows for receiving, storing, and manipulating data of the dentalpractice.

In various embodiments, first user system 102 and/or applicationsrunning on the system may communicate with a dental integration platform(DIP) 108. For example, first user system 102 can transmit data relevantto the operation of the dental practice to DIP 108, and the data can betransformed, formatted, stored, and processed by DIP 108. In variousembodiments, data stored within a database of a DPMS utilized by firstuser system 102 is provided to DIP 108.

First user system 102 and DIP 108 may, for example, communicate over anetwork. As used herein, the term “network” includes any cloud, cloudcomputing system or electronic communications system or method whichincorporates hardware and/or software components. Communication amongthe various systems may be accomplished through any suitablecommunication channels, such as, for example, a telephone network, anextranet, an intranet, Internet, online communications, satellitecommunications, off-line communications, wireless communications, localarea network (LAN), wide area network (WAN), virtual private network(VPN), networked or linked devices and/or any suitable communication ordata input modality. Moreover, although the systems described herein maytypically be implemented with TCP/IP communications protocols, thesystem may also be implemented using IPX, Appletalk, IP-6, NetBIOS, OSI,any tunneling protocol (e.g. IPsec, SSH), or any number of existing orfuture protocols. If the network is in the nature of a public network,such as the Internet, it may be advantageous to presume the network tobe insecure and open to eavesdroppers. Specific information related tothe protocols, standards, and application software utilized inconnection with the Internet is generally known to those skilled in theart and, as such, need not be detailed herein. See, for example, DilipNaik, Internet Standards and Protocols (1998); Java 2 Complete, variousauthors, (Sybex 1999); Deborah Ray and Eric Ray, Mastering HTML 4.0(1997); and Loshin, TCP/IP Clearly Explained (1997) and David Gourleyand Brian Totty, HTTP, The Definitive Guide (2002), the contents ofwhich are hereby incorporated by reference.

A network may be unsecure. Thus, communication over the network mayutilize data encryption. Encryption may be performed by way of any ofthe techniques now available in the art or which may becomeavailable—e.g., Twofish, RSA, El Gamal, Schorr signature, DSA, PGP, PKI,GPG (GnuPG), and symmetric and asymmetric cryptosystems.

In various embodiments, one or more components of DIP 108 can comprisecloud-based modules and/or components. As will be described in furtherdetail, components of DIP 108 such as data transmitting modules,databases, data processing modules, application servers, and interfacescan be cloud-based components. Although they are described andillustrated as discrete components, one or more of the components of DIP108 can be combined with one another, or distributed among one or morecloud-based computing systems.

In various embodiments, first user system 102 comprises an applicationconfigured to transmit data from first user system 102 to DIP 108. Forexample, first user system 102 may comprise an upload applicationprogramming interface (API) which transmits data to DIP 108. The uploadAPI can transmit data from first user system 102 to DIP 108 in responsea request from DIP 108, or the upload API can be programmed to transmitdata to DIP 108 under predetermined circumstances, including at orduring a particular time or interval of time. Any manner of transmittingdata from first user system 102 to DIP 108, including any software orhardware, is within the scope of the present disclosure.

In various embodiments, DIP 108 comprises a data transmitting module110. For example, data transmitting module 110 may receive datatransmitted from first user system 102 to DIP 108. Data transmittingmodule 110 may be in communication with a formatted database 111, andmay transmit data received from first user system 102 to formatteddatabase 111.

Data transmitting module 110 may, for example, comprise a conversionengine configured to receive data from first user system 102 and formatthe data for storage within formatted database 111. For example, datatransmitting module 110 can receive the data transmitted by the DPMS offirst user system 102 and transmit it for storage within formatteddatabase 111.

With reference to FIG. 1B, system 100B can comprise multiple formatteddatabases 111. For example, system 100B can comprise a system database111A, a periodic trend database 111B, an issue database 111C, a contentdatabase 111D, or any combination of multiple databases, includingmultiple databases of the same type. Databases, such as databases111A-111D, can comprise SQL (relational) databases, NoSQL(non-relational databases), or any combination (e.g., hybrid databases).For example, one or more of databases 111A-111D can comprise NoSQLdatabases such as column store databases, key-value store databases,document store databases, graph databases, multivalue databases,multimodel databases, or other NoSQL databases. In various embodiments,one or more of databases 111A-11D comprise analytic databases. Further,one or more of databases 111A-111D can comprise cloud-based databases,including cloud-based relational databases (such as, for example, AmazonRedshift, Amazon Aurora.MySQL, MariaDB, Oracle Database, or SQL Server)and cloud-based non-relational databases (such as, for example,SimpleDB, DynamoDB, MongoDB, or CosmosDB. The use of any combination ofrelational and non-relational, and cloud-based or locally-hosteddatabases, is within the scope of the present disclosure. Further,databases 111A-111D may run on data transmitting module 110, a dedicatedcomputing device of DIP 108, another shared computing device of DIP 108,or any other computing device in electronic communication with DIP 108.

In various embodiments, data transmitting module 110 may request datafrom first user system 102 under predetermined circumstances. Forexample, data transmitting module 110 may request data from first usersystem 102 at predetermined intervals of time, such as every hour, everyhalf hour, every 10 minutes, every 5 minutes, every 90 seconds, and/orevery 1 minute. Further, data transmitting module 110 may request onlydata which has been entered or changed since a previous query. Forexample, data transmitting module 110 may be configured to request anynew or changed data from first user system 102 every 90 seconds.Although described with reference to specific predeterminedcircumstances and time intervals, any manner of transmitting data fromfirst user system 102 to data transmitting module 110 is within thescope of the present disclosure.

One skilled in the art will also appreciate that, for security reasons,any databases, systems, devices, servers or other components of thesystem may consist of any combination thereof at a single location or atmultiple locations, wherein each database or system includes any ofvarious suitable security features, such as firewalls, access codes,encryption, decryption, compression, decompression, and/or the like.

In various embodiments, DIP 108 further comprises a data processingmodule 112 in communication with formatted database 111. Data processingmodule 112 may, for example, retrieve data from formatted database 111,perform operations on the data, and write to formatted database 111newly created and/or processed data for storage and subsequentretrieval. Data processing module 112 may be an application running ondata transmitting module 110, a dedicated computing device of DIP 108,another shared computing device of DIP 108, or any other computingdevice in electronic communication with DIP 108.

Data processing module 112 may comprise, for example, one or moresoftware applications. In various embodiments, data processing module112 comprises software applications configured to process datatransmitted from first user system 102 and return relevant data toformatted database 111. For example, data processing module 112 canaccess formatted data transmitted by first user system 102 and storedwithin formatted database 111, and the software applications of dataprocessing module 112 can manipulate and process the data to produce anumber of data sets, including one or more sets of revenue data,schedule data, patient data, or other data. The newly-created data setscan be stored in formatted database 111. Data processing module 112 maythus generate models and analysis of individual dental practices as thepractices relate to the models and thereby generate insight into theindividual dental practices.

In various embodiments, DIP 108 further comprises an application server113. Application server 113 may, for example, transmit data from dataprocessing module to interfaces outside of DIP 108. For example,application server 113 can host web sites and provide backend supportfor web applications. In various embodiments, application server 113 isconfigured to transmit data, including newly-created data, fromformatted database to one or more user interfaces.

With reference back to FIG. 1B, system 100B can comprise, for example,multiple application servers 113. In various embodiments, system 100Bcomprises one or more of a user interface application server, aconsultant interface application server, a dashboard application server,an action center application server, or any combination of applicationservers, including multiple application servers of the same type.

In various embodiments, the dental practice utilizing first user system102 can access, via a network (including the internet), a first userinterface 115. For example, application server 113 can display data tofirst user system 102 through first user interface 115. Further, firstuser interface 115 can be used to transmit commands or requests to othercomponents of system 100B, through, for example, application server 113.

In various embodiments, first user interface 115 comprises a graphicaluser interface. For example, with reference to FIG. 2, a first userinterface 115 comprising a graphical user interface dashboard 200 isillustrated. In various embodiments, dashboard 200 provides visualrepresentation of data that has been formatted, processed, created, andotherwise manipulated by DIP 108. Visual representations of data cancomprise text, symbols, graphical representations, and any otherrepresentation that can be perceived visually. For example, one or moresets of revenue data, schedule data, patient data, or other data can bevisually represented by first user system 102 and/or data transmittingmodule 110 to employees of the dental practice. Dashboard 200 mayprovide a landing screen for a dental practice, from which one maynavigate to the various applications and interfaces described herein.

In various embodiments, first user interface 115 comprises a non-visualuser interface. For example, first user interface 115 may comprise avoice user interface. Although further described with reference tospecific embodiments (for example, graphical user interfaces) any typeof interface is within the scope of the present disclosure.

Further, first user interface 115 can comprise a data interface. Forexample, first user interface 115 can comprise a machine-implementedmodule, such as a machine learning module, an artificial intelligenceinterface, an API, a file transfer protocol client, or any otherprogrammable interface which allows for machine-to-machinecommunication.

With reference to FIG. 1A, system 100A may comprise a second userinterface 116 and/or a third user interface 117. In various embodiments,each of first user interface 115, second user interface 116, and thirduser interface 117 is configured to display, convey, or otherwisecommunicate information relevant to their respective user systems (firstuser system 102, second user system 104, and third user system 106).Although described with reference to specific user systems andinterfaces (first, second, and third user systems and interfaces), theuse of any number of user systems and user interfaces is within thescope of the present disclosure.

With reference to FIG. 1C, a system 100C in accordance with variousembodiments is illustrated. System 100C can comprise, for example, firstuser system 102. First user system 102 comprises a computer based systemlocated in a dental office which utilizes a DPMS. In variousembodiments, the DPMS comprises a database that is the system of recordfor data stored within first user system 102, e.g., data relating to thedental practice such as patient data, treatment data, financial data,and business operation data.

First user system 102 can, for example, communicate with datatransmitting module 110 of system 100C. In various embodiments, firstuser system 102 can provide data transmitting module 110 with data inthe native format of the DPMS, i.e., not formatted for system 100C. Datatransmitting module 110 can convert data in the native format of theDPMS to data of the format utilized by the components of DIP 108. Inthat regard, fields from the database or data store of a DPMS may bemapped and migrated into a database or data store having a schemasuitable to support DIP 108. One or more fields from the DPMS may beread and processed into a format suitable for DIP 108, The result of theprocessed data from the DPMS may then be written into DIP 108. In otherembodiments, first user system 102 can comprise a conversion applicationwhich converts the data from the native format of the DPMS to the formatanticipated and utilized by system 100C.

In various embodiments, system 100C further comprises system database111A. System database 111A can, for example, be in communication withand capable of receiving data from data transmitting module 110A. Invarious embodiments, system database 111A can store data from multipledifferent user systems, in a common format.

System 100C can further comprise, for example, a logic data processingmodule 112A. For example, logic data processing module 112A can be incommunication with system database 111A and perform logic operations onthe data stored within systems database 111A.

In various embodiments, system 100C further comprises a dashboardapplication server 113A. For example, dashboard application server 113Acan be in communication with logic data processing module 112A. Further,dashboard application server 113A can be in communication with firstuser interface 115. In such embodiments, dashboard application server113A can transmit data for display on first user interface 115, and canreceive commands, requests, and instructions from a user through firstuser interface 115.

Dashboard application server 113A can, for example, be in communicationwith a periodic trend database 111B. In various embodiments, periodictrend database 111B can receive and store data captured by system 100Cfrom first user system 102 at various points in time, and store suchdata chronologically. For example, periodic trend database 111B maycapture a set or subset of data at a specific point in time (e.g., asnapshot) at specific intervals of time.

System 100C can further comprise, for example, a key findings andopportunity report data processing module (“KFOR”) 112B. KFOR 112B can,for example, be in communication with an issue database 111C. In variousembodiments, KFOR 112B can be in communication with an action centerapplication server 113B. Action center application server 113B can, forexample, deliver content, receive commands and instructions, and bevisually represented on the first user interface 115. Although describedwith reference to a particular type of data processing module (i.e., theKFOR) any type of data processing module can be utilized in connectionwith action center application server 113B.

Action center application server 113B can, for example, be incommunication with a consultant interface 109. In various embodiments,action center application server 113B can transmit data to be displayed,conveyed, or otherwise communicated by consultant interface 109, and canreceive commands, requests, and instructions from a user (e.g., aconsultant) through consultant interface 109.

In various embodiments, consultant interface 109 can comprise amachine-to-machine interface. Similar to user interfaces 115, 116, and117, consultant interface 109 can comprise a machine learning module, anartificial intelligence module, an API, a file transfer protocol client,or any other programmable machine-to-machine interface.

With reference to FIG. 3, an exemplary software application (treatmentapplication 307) running within data processing module 112 isillustrated. Treatment application may provide support for dashboard 200of FIG. 2 and/or other interfaces by retrieving, analyzing, andproviding data to populate the various fields and displays of theinterfaces. For example, treatment application 307 can retrieve a set offormatted patient data 305 from formatted database 111 for processing.In various embodiments, formatted patient data 305 comprises informationsuch as patient names, ages, sex, histories of treatments performed bythe dental practice, histories of treatments performed by other dentalpractices, and other information relating to patients of the dentalpractice.

Treatment application 307 can, for example, process formatted patientdata 305 for each patient of the dental practice, and create a set oftreatment data 309. In various embodiments, treatment data 309 comprisesa treatment plan for each patient of formatted patient data 305.Treatment plans can comprise one or more recommended treatments for aparticular patient, including recommended dates for scheduling of thetreatment. Treatment data 309 may further comprise projected financialdata, such as projected revenue and/or projected expenses, based on thetotal number and types of treatments and/or treatment estimatescontained in treatment data 309.

In various embodiments, treatment data 309 is stored within formatteddatabase 111, where it can be stored and/or retrieved by applicationserver 113. Application server 113 may, for example, prepare and formattreatment data 309 for transmittal to first user interface 115.

With reference to FIG. 3, a UI 300 may, for example, visually representand communicate various aspects of treatment data 309. For example, UI300 may visually represent a planning efficiency of treatment data 309.In various embodiments, planning efficiency comprises a comparison ofpotential revenue generated by the treatment recommendations oftreatment data 309 with other aspects of treatment data 309, includingthe total of treatments accepted and/or scheduled, and the total oftreatments completed and/or performed by the dental practice. Theinformation presented may indicate the importance of effectivescheduling and follow up.

In various embodiments, UI 300 can represents (for example, visually) aprojected revenue corresponding to treatment data 309. The projectedrevenue may, for example, comprise an estimate of revenue that will becollected in a specified time frame based on, in part, the total oftreatments accepted and/or scheduled and the total of treatmentscompleted and/or performed by the dental practice. As described inconnection with user interfaces 115, 116, and 117, UI 300 can comprise anon-visual interface, such as a voice interface, and/or amachine-to-machine interface, among other interfaces.

Although described with reference to specific data types (for example,planning efficiency, projected revenue, and procedure profiler),treatment data 309 can comprise any data calculated or created from, atleast in part, formatted patient data 305. Further, UI 300 candemonstrate (for example, visually) any or all aspects of treatment data309, including only those aspects of treatment data 309 predeterminedand/or selected by the dental practice. Further, UI 300 may, forexample, be configured to visually represent different aspects oftreatment data 309 based on a particular user (e.g., a specific employeeof the dental practice).

With reference to FIG. 4, another exemplary software application(schedule application 417) running within data processing module 112 isillustrated. For example, schedule application 417 can receive formattedpatient data 305 from formatted database 111 for processing. Aspreviously described, formatted patient data 305 may comprise, forexample, information such as patient names, ages, sex, histories oftreatments and procedures performed by the dental practice, histories oftreatments performed by other dental practices, currently-scheduledtreatments, and other information relating to patients of the dentalpractice.

Schedule application 417 may, for example, process formatted patientdata 305 for each patient of the dental practice, and create a set ofschedule data 419. In various embodiments, schedule data 419 comprises adaily schedule which includes each treatment planned for each patient ona specified day. Daily schedules of schedule data 419 may comprise oneor of an individual schedule, wherein the individual schedule includeseach and every treatment assigned and/or scheduled to be performed by aparticular user (e.g., employee of the dental practice). Stated anotherway, schedule data 419 may comprise a daily schedule of treatments to beperformed by each employee of the dental practice. Schedule data 419 maybe accompanied by suggestions for improvement in practice managementand/or practical skills based on comparison of the subject dentalpractice with peers at peer dental practices.

In various embodiments, formatted patient data 305 transmitted toschedule application 417 can comprise data from a plurality of usersystems, including first user system 102, second user system 104, and/orthird user system 106. Schedule application 417 may, for example,generate one or more schedule models (within schedule data 419) fromformatted patient data 305. In various embodiments, the schedule modelsof schedule data 419 comprise one or more of an average time period fromplanned to accepted (T_(PA)), an average time period from accepted toscheduled (T_(AS)), an average time period from scheduled to completed(T_(SC)), and an average time period from planned to completed (T_(PC))of the various applicable dental practices, wherein the averages aretaken across the plurality of user systems.

Multiple schedule models may be generated for the purposes of comparinga single dental practice (such as, for example, the dental practiceutilizing first user system 102) to a plurality of other dentalpractices (such as, for example, the dental practices using second usersystem 104 and third user system 106). In various embodiments, theindividual dental practices included in the plurality of dentalpractices are selected based on one or more predeterminedcharacteristics. For example, one or more schedule models can begenerated by processing the patient data of dental practices sharing oneor more characteristics with an individual dental practice, includingnumber of patients, geographical market, number of service providers,number of employees, age of operation of practice, and other relevantcharacteristics. In that regard, dental practices may be categorizedbased on characteristics (e.g., demographics) of dental practices andcompared to dental practices within the same or similar demographicgroups.

After one or more schedule models are generated, schedule application417 can compare the models to schedule data 419 of first user system102, and generate a set of schedule comparison data. One or more aspectsof the set of schedule comparison data may, for example, be transmittedor visually represented to a UI 400 and/or first user interface 115.

In various embodiments, schedule data 419 is transmitted to formatteddatabase 111, where it can be retrieved by data transmitting module 110and/or application server 113. Application server 113 may, for example,prepare and format schedule data 419 for transmittal to UI 400 and/orfirst user interface 115.

With reference to FIGS. 5 and 6, a UI 500A and UI 500B may represent(for example, visually) various aspects of schedule data 419. Forexample, UI 500A may visually represent a daily schedule 521 of scheduledata 419. In various embodiments, daily schedule 521 comprises a list ofall treatments scheduled for a specified day, as well as the patientcorresponding to each treatment, and the provider (e.g., employee of thedental practice) assigned to carry out the treatment.

For example, UI 500B may visually represent an historical efficiencyfunnel 633, and/or a planning efficiency 635. In various embodiments,each of historical efficiency funnel 633 and/or planning efficiency 635are created from analysis of formatted patient data 111 and/or scheduledata 419, and can be displayed, conveyed, or otherwise communicated toone or more users, such as employees of the dental practice.

Although described with reference to particular aspects of schedule data419, UI 500A and/or UI 500B can be configured to represent any aspect ofschedule data 419 based on a particular user (e.g., an employee of thedental practice), as well as any other criteria.

In various embodiments, system 100 comprises a plurality of usersystems. Each user system, such as second user system 104 and third usersystem 106, transmits data to and from the same DIP 108. In variousembodiments, first user system 102, second user system 104, and/or thirduser system 106 utilize different data formats, software, and/orhardware from each other. In such embodiments, data transmitting module110 can be configured to receive data in different formats from one ormore user systems 102, 104, and 106, and convert and/or format the datato a common format for storage within database 111.

In various embodiments having more than a single user system (e.g.,first user system 102), DIP 108 can comprise more than one datatransmitting module 110 and/or more than one formatted database 111.Although illustrated with reference to a single data transmitting module110 and a single formatted database 111 (as well as three user systems),one having skill in the art will appreciate that a larger number of usersystems may scale into the system by incorporating additional datatransmitting modules 110 and/or databases 111.

User systems (such as 102, 104, and/or 106) can transmit to DIP 108identifiable characteristics of the dental practice utilizing each ofthe user systems. For example, first user system 102, second user system104, and/or third user system 106 can each transmit to DIP 108 variouscharacteristics of their respective dental practices, including numberof patients, geographical market, number of service providers, number ofemployees, age of operation of practice, and other relevantcharacteristics. As will be described in further detail, theidentifiable characteristics of the dental practice utilizing each ofthe user systems may be used to compare dental practices having similarcharacteristics in a quantitative manner.

With reference to FIG. 7, yet another exemplary software application(financial application 725) running within data processing module 112 isillustrated. For example, financial application 725 can receiveformatted patient and financial data 723 from formatted database 111 forprocessing. Formatted patient and financial data 723 can comprise, inpart, formatted patient data 305 (of FIGS. 3 and 5), as well asformatted financial data (e.g., revenue and/or expense data) of thedental practice.

In various embodiments, similarly to schedule application 417, financialapplication 725 may generate financial projections based on formattedpatient and financial data 723. For example, financial application 725may generate one or more parameters or factors that may then be used togenerate financial projections for the dental practice. For example, thefactors or parameters generated by financial application 725 may includeone or more of a potential revenue of planned to accepted ($R_(PA)), apercentage revenue of planned to accepted (% R_(PA)), a potentialrevenue of accepted to scheduled ($R_(AS)), a potential revenue ofscheduled to completed ($R_(SC)), and a percentage revenue of acceptedto completed (% R_(AC)). These factors may, for example, be generatedusing formatted patient and financial data 723 corresponding toyear-to-date data (e.g., data generated from the first day of thepresent year to the present date on which the financial application 725is generating the factors).

After generating one or more factors, financial application 725 canutilize the factors to calculate projected financials. For example,financial application 725 can generate projected revenues and/orexpenses for a predetermined time frame, such as a quarter, a year, orany desired period, or financial application 725 can generate projectedrevenues and/or expenses for selected time frames based on a start andstop date input by a user of first user system 102. For example,financial application 725 can generate one or more of a projectedtreatment revenue, a projected accepted revenue, a projected completedrevenue, and/or various expense data for any predetermined time period.

In various embodiments, formatted patient and financial data 723 cancomprise data from a plurality of user systems, including first usersystem 102, second user system 104, and/or third user system 106.Financial application 725 may, for example, generate one or morefinancial models 727 from formatted patient and financial data 723. Invarious embodiments, financial models 727 comprises one or more of anaverage annual potential revenue, an average annual accepted revenue, anaverage completed revenue, various expense data, an average T_(PA), anaverage T_(AS), an average T_(SC), and an average T_(PC) of the variousapplicable dental practices, wherein the average is taken across theplurality of user systems.

Multiple financial models may be generated for the purposes of comparinga single dental practice (such as, for example, the dental practiceutilizing first user system 102) to a plurality of other dentalpractices. In various embodiments, each of the dental practices of theplurality of dental practices are selected based on a predeterminedcharacteristic. For example, one or more financial models can begenerated by processing the patient and financial data of dentalpractices sharing one or more characteristics with an individual dentalpractice, including number of patients, geographical market, number ofservice providers, number of employees, age of operation of practice,and other relevant characteristics.

After one or more financial models are generated, financial application725 can compare the models to financial model 727 of first user system102, and generate a set of financial comparison data. One or moreaspects of the set of financial comparison data may, for example, betransmitted or visually represented to first user interface 115.

In various embodiments, financial model 727 is transmitted to formatteddatabase 111, where it can be retrieved by data transmitting module 110and/or application server 113. Application server 113 may, for example,prepare and format financial model 727 for transmittal to first userinterface 115.

With reference to FIGS. 7 and 8, a UI 700 may, for example, visuallyrepresent and communicate various aspects of financial model 727. Forexample, UI 700 may visually represent a current receivables category729 of financial model 727. Current receivables category 729 maycomprise, for example, one or more revenue projections, includingprojections based on financial model 727 generated by financialapplication 725.

In various embodiments, UI 700 visually represents a collectionefficiency category 731 of financial model 727. Collection efficiencycategory 731 may, for example, comprise total revenue collected for apredetermined time frame, total adjustments to billings made to patientsfor a predetermined time frame, total outstanding billings made topatients for a predetermined time frame, and any othercollection-related data of financial model 727.

Although described with reference to specific data types (currentreceivables category 729 and collection efficiency category 731),financial model 727 can comprise any data calculated or created from, atleast in part, patient and financial data 723. Further, UI 700 canvisually demonstrate any or all aspects of financial model 727,including only those aspects of financial model 727 predetermined and/orselected by the dental practice. Further, UI 700 may, for example, beconfigured to visually represent different aspects of financial model727 based on a particular user (e.g., an employee of the dentalpractice).

With reference to FIG. 1, system 100 can further comprise one or moreconsultant user interfaces 109. In various embodiments, consultant userinterface 109 is in communication with DIP 108. Consultant userinterface 109 may, for example, access data processing module 112 and/orformatted database 111. As previously noted, consultant user interface109 can comprise a human operated interface (such as a GUI or other UI),or a machine-to-machine interface, such as a machine learning module, anartificial intelligence interface, an API, a file transfer protocolclient, or any other programmable interface which allows formachine-to-machine communication.

In various embodiments, consultant user interface 109 may access datatransmitted from a number of user systems, including first user system102, second user system 104, and/or third user system 106, and to firstuser interface 115, second user interface 116, and/or third userinterface 117. For example, consultant user interface 109 may accessdata, including treatment data (e.g., treatment data 309), schedule data(e.g., schedule data 419), and/or revenue data (e.g., financial model727) for one or more user systems. In various embodiments, consultantuser interface 109 can be utilized by a user (i.e., a consultant)capable of reviewing various data of dental practices and makingrecommendations for improvement. For example, a consultant utilizingconsultant user interface 109 to analyze the data of first user system102 may qualitatively analyze one or more of treatment data, scheduledata, and revenue data to provide recommendations for improving one ormore aspects of the performance of the dental practice.

In various embodiments, a user utilizing consultant user interface 109may determine which aspects of treatment data, schedule data, revenuedata, or other relevant data generated by DIP 108, is transmitted to oneor more user interfaces. For example, consultant user interface 109 maydirect data transmitting module 110 to transmit and/or visuallyrepresent data to first user interface 115, including a schedule modelof schedule data 419 and/or financial model 727.

In other embodiments, consultant user interface 109 comprises amachine-to-machine interface which determines which data (such astreatment data, schedule data, and/or financial data) is transmitted tovarious components of system 100.

With reference to FIGS. 1 and 9, a method 900 for operating a DIP (suchas DIP 108) in accordance with various embodiments is illustrated. Forexample, method 900 may comprise a receive and format first user datastep 932. In various embodiments, step 932 comprises first user system102 transmitting data relevant to the operation of the dental practiceto DIP 108, and the data is then formatted, stored, and processed by DIP108.

In various embodiments, method 900 further comprises a generatefinancial model and schedule model step 934. For example, step 934 maycomprise a data processing module (such as data processing module 112)generating one or more financial models and schedule modules from dataprovided by first user system 102., e.g., based on data provided bymultiple other dental practices.

Method 900 may further comprise, for example, a compare first user datato financial model step 936. In various embodiments, step 936 maycomprise a data processing module (such as data processing module 112)comparing data provided by first user system 102 to one or morefinancial models generated by step 934.

In various embodiments, method 900 further comprises a compare firstuser data to schedule model step 938. For example, step 938 may comprisea data processing module (such as data processing module 112) comparingdata provided by first user system 102 to one or more schedule modelsgenerated by step 934.

Method 900 may further comprise, for example, a transmit financialcomparison data and schedule comparison data to first user system step940. In various embodiments, step 940 comprises transmitting comparisondata created in steps 936 and 938 to first user interface 115.

With reference to FIGS. 1C and 10, a method 1000 for improvingoperations of a dental practice in accordance with various embodimentsis illustrated. For example, method 1000 can utilize systems 100A, 100B,and/or 100C of FIGS. 1A-1C to identify issues with the operation of adental practice.

In various embodiments, method 1000 comprises a step 1042 of receivingsnapshot data from a DPMS. For example, DIP 108 can receive from firstuser system 102 a data set the DPMS that is captured at a particularpoint in time (e.g., a snapshot). The data can comprise any relevantdata from the operation of the dental practice that is stored within theDPMS, including, for example, any of patient data, treatment plans,schedule data, financial data (including revenue and/or expenses),treatment data (including total of treatments accepted and/or scheduled,and the total of treatments completed and/or performed by the dentalpractice), treatment planning, accepting, and completion rates,potential revenue of planned to accepted ($R_(PA)), a percentage revenueof accepted to scheduled (% R_(AS)), a potential revenue of scheduled tocompleted ($R_(SC)), and a percentage revenue of planned to completed (%R_(PC)). The snapshot data can be transmitted by data transmittingmodule 110 to system database 111A.

Method 1000 can further comprise, for example, a step 1044 of analyzingmetrics from the snapshot data. In various embodiments, specificelements of the snapshot data can be compared to data stored withinsystem database 111A. For example, system database 111A can comprisedata models, against which elements of the snapshot data can becompared. With reference back to FIG. 9, system database 111A cancomprise one or more of a financial model and a schedule model, asgenerated in step 934 of method 900. Although described with referenceto specific models, step 1044 can comprise comparing any element of thesnapshot data with any reference or reference value within systemdatabase 111A, including models generated by DIP 108.

Step 1044 can further comprise identifying, through analysis by, forexample, logic data processing module 112A, one or more metrics,elements, or aspects of the dental practice of the first user that are apredetermined magnitude or amount less than a threshold or predictedvalue. For example, one or more metrics of the dental practice, such asan actual revenue, may be significantly less than a projected revenuefor the dental practice. Step 1044 can comprise noting any and allmetrics, elements, or aspects of the snapshot data that are apredetermined magnitude less than anticipated values.

In various embodiments, metrics of the snapshot data can be compared tocorresponding goal metrics stored within, for example, system database111A. In such embodiments, goal metrics can comprise an aspirational,expected, anticipated, calculated, or otherwise projected value for aspecific metric over a desired time frame. For example, a goal metriccan comprise a goal percentage revenue of planned to completed (%R_(PC)) over a specified time frame, such as 30 days, 60 days, 90 days,or any other suitable time interval. The metric of snapshot data (%R_(PC)) is compared to the goal metric % R_(PC) over a specified timeinterval. If the metric % R_(PC) of the snapshot data is a specifiedvalue or magnitude less than the goal metric % R_(PC), the metric can beflagged for use in determining potential operation issues of thepractice. Although illustrated with respect to a specific metric (%R_(PC)), step 1044 can comprise analyzing a multitude of metrics of thesnapshot data. Goal metrics, for example, can be calculated and/ordetermined based on characteristics of the practice. For example, one ormore goal metrics can be generated by processing the data of dentalpractices sharing one or more characteristics with an individual dentalpractice, including number of patients, geographical market, number ofservice providers, number of employees, age of operation of practice,and other relevant characteristics. In that regard, dental practices maybe categorized based on characteristics (e.g., demographics) of dentalpractices and compared to dental practices within the same or similardemographic groups. In other words, goal metrics for a particularpractice can be calculated from the performance and health (i.e.,financial success) of other similar practices.

Further, goal metrics can be calculated or determined based on theperformance and health (i.e., financial success) of non-similarpractices. For example, particular metrics (for example, return oninvestment, profit margin ratio, and/or return on sales) can bedetermined and stored by the system independently of characteristics ofthe individual practice. Stated another way, goal metrics may comprise“standard” metrics that used to evaluate the performance and health ofmost or all dental practices. Although described with reference tospecific methods of calculating goal metrics, the use of any type ofgoal metric, for any specified time interval, is within the scope of thepresent disclosure.

With reference to FIG. 11, a UI 1100 illustrates a revenue goal 1141. Invarious embodiments, revenue goal 1141 is stored, for example, withinsystem database 111A. For example, step 1044 can comprise comparing ormore metrics of the snapshot data to revenue goal 1141. Further, UI 1100can display, convey, or otherwise communicate information regardingrevenue goal 1141 and any related metrics or numerical values, such as aprojected revenue, a current year-to-date revenue, a projected treatmentplan revenue, or any other related numerical value.

With reference to FIG. 12, a UI 1200 illustrates a patient base goal1143. For example, patient base goal 1143 can comprise a goal of thetotal number of patients of a dental practice determined, at leastpartially, by examining the patient base of a plurality of other dentalpractices sharing one or more characteristics or demographics with thedental practice utilizing systems 100A-100C. Step 1044 can comprisecomparing one or more metrics of the snapshot data (such as the totalnumber of patients of the dental practice) to patient base goal 1143.Further, UI 1200 can display, convey, or otherwise communicateinformation regarding patient base goal 1143 and any related metrics ornumerical values, such as a number of new patient, a number ofreactivated patients, a number of inactive patients, a number ofpatients at risk of becoming inactive, or any other related numericalvalue.

In various embodiments, method 1000 further comprises a step 1046 ofidentifying an operational issue. For example, step 1046 can comprisingtransmitting one or more metrics of the snapshot data that are belowtheir respective anticipated, goal, and/or threshold values. In suchembodiments, step 1046 can comprise utilizing KFOR 112B to identify anoperational issue by comparing the metrics determined in step 1044 withone or more issue profiles stored, for example, within issue database111C. In various embodiments, KFOR 112B can produce a report identifyingand describing the operational issues, such as, for example, a keyfindings and opportunity report. Although described with reference to aparticular type of data processing module (i.e., the KFOR) any type ofdata processing module can be utilized to identify an operation issue.

In various embodiments, an issue profile can comprise a list of metricswhich deviate from their respective anticipated, goal, and/or thresholdvalues, and a particular issue which the deviations implicate. Forexample, step 1044 can determine that a hygiene retention rate is 70%and the projected revenue is 4% below the corresponding goal metric, andtransmit these metrics to KFOR 112B. KFOR 112B can compare these metricswith the issue profiles in issue database 111C, and determine that thesetwo metrics are associated with an issue profile that denotes a failureto retain patients for dental hygiene procedures. Further, this issuemay be indicated on the key findings and opportunity report.

If no operational issues are identified in step 1046, method 1000 cancomprise a step 1048 of storing the snapshot data in system data base1048. For example, the snapshot data received in step 1042 can be storedwithin the system database 111A of DIP 108. As previously described, thesnapshot data may be combined with the data of other dental practices,sharing one or more elements of demographic data, to create and/orimprove models stored within and used by DIP 108. Further, method 1000can comprise a step 1050 of storing the snapshot data in trend database111B.

In various embodiments, method 1000 further comprises a step 1052 ofidentifying a proposed solution. For example, for each of the issuesidentified in step 1046, DIP 108 can determine one or more proposedsolutions to each issue. Step 1052 can comprise identifying a potentialchange or series of changes to be undertaken by the dental practice toaddress the issue identified in step 1046. Further, step 1052 cancomprise comparing the issue(s) identified in step 1046 with, forexample, content stored within content database 111D, and creating oneor more proposed solutions to address the issues.

Method 1000 can further comprise, for example, a step 1054 of confirmingthe proposed solutions. For example, step 1054 can comprise transmittingthe proposed solutions to a consultant interface 109, where the proposedsolutions are evaluated by a consultant. Any data or informationrelevant to the proposed solutions may also be displayed, conveyed, orotherwise communicated to the consultant. For example, the indicatorstransmitted in step 1044, the issue profile, and the proposed solutioncan be communicated to the consultant. In various embodiments, theconsultant can review and confirm each of the proposed solutions fromstep 1054.

In other embodiments, step 1054 comprises confirming the proposedsolution via a machine-to-machine interface 109. For example, step 1054can comprise confirming, by a machine learning interface, an artificialintelligence interface, or any other suitable machine-to-machineinterface capable of automatically confirming the proposed solutionwithout input from the consultant.

In various embodiments, method 1000 can comprise a step 1056 oftransmitting the confirmed solution to the first user. For example, eachof the solutions confirmed in step 1054 are transmitted, for example, tothe first user interface 115. In various embodiments, the solutions aredisplayed, conveyed, or otherwise communicated to first user interface115 by the action center application server 113B. Step 1056 comprisesproviding any aspect of the confirmed solution, including links tocontent (such as content stored within content database 111D) andinstructions, necessary for the first user to implement the solution inthe dental practice and the DPMS of the first user system 102.

Method 1000 further comprises, for example, a step 1058 of implementingthe solutions. In various embodiments, step 1058 comprises the firstuser reviewing the content (such as content stored within contentdatabase 111D) and instructions provided by step 1056, and subsequentlyimplementing any recommended changes. For example, if (as previouslydescribed) the dental practice is experiencing the issue of “failure toretain patients for dental hygiene procedures,” step 1058 may indicateto the first user that employees (such as the dental hygienists and/orschedulers) should undertake training to improve their ability to “sell”hygiene procedures. Such training content is provided to the first uservia the content database 111D and the first user interface 115.

In other embodiments, step 1058 comprises implementing the proposedsolution by, for example, a machine learning module, an artificialintelligence module, or any other automatic and computer implementedmodule, program, subroutine, or interface. In such embodiments, theproposed solution is not evaluated by a human (such as first user).Instead, the proposed solution is evaluated by the computer implementedmodule, program, subroutine, or interface, and if the solution meets aset of predetermined criteria, the solution is implemented. Thepredetermined criteria can comprise any suitable measure of thepotential effectiveness of the proposed solution, including, amongothers, the historical effectiveness of the solution in other practicesincluding practices sharing one or more characteristics or demographicswith the individual practice.

In various embodiments, method 1000 further comprises a step 1060 ofevaluating the solution. Step 1060 can comprise, for example, obtainingfurther snapshot data (i.e., “trend data”) from the first user system102 at specific time periods after the implementation of the solution(such as, for example, step 1058). For example, trend data can bereceived by DIP 108 at periods of 30, 60, 90, and 120 days or longerafter implementation of the solution. Although described with referenceto specific time periods, any frequency of obtaining trend data iswithin the scope of the present disclosure. The trend data may be, forexample, a series of data points that include metric values and/or anindicators at a corresponding time and/or date. In that regard, trenddata may be represented as a set of tuples (e.g., [60%, Jan. 1, 2017],[68%, Jan. 15, 2017], [79%, Feb. 1, 2017], [83%, Mar. 1, 2017]). Thetrend data may thus be illustrative of changes in performance metricsover time suitable for analysis to identify whether a solution had apositive, negative, or negligible impact on the metrics.

Trend data can be compared for example, by logic data processing module112A, to expected change and/or improvement in the metric or metrics towhich the solution is directed. In various embodiments, an expectedchange and/or improvement can include both a magnitude of change orimprovement as well as a corresponding time interval. For example, inthe scenario described previously (the issue of a failure to retainpatients for dental hygiene procedures), a solution can be associatedwith an expected improvement of the hygiene retention rate from 70% (asmeasured in the snapshot data) to 75%, and the projected revenue from 4%less than the goal metric to meeting the goal metric (i.e., zero % lessthan the goal metric) with 90 days. Step 1058 can comprise evaluatingthe trend data at 90 days after implementation of the solution, andcomparing the hygiene retention rate and projected revenue of the trenddata to the expected values of the solution. If the hygiene retentionrate and/or projected revenue are at higher than the expected values ofthe solution, the solution is determined to be successfully. Anunsuccessful solution would result in either no change or an increase inthe indicators identified during step 1044.

Step 1060 can further comprise modifying issue database 111C to reflectthe success or failure of the implemented solutions. In variousembodiments, if a solution is determined to be successful, step 1060 canmodify the issue profile of the specific issue to reflect additionalsuccess, specifically, success in the dental practice of the first user.If a solution is determined to be unsuccessful, the issue profile of thespecific issue may be modified to reflect the lack of success of theimplemented solution, and, potentially, to not propose the solution foraddressing the specific issue in the future.

In various embodiments, step 1060 comprises evaluation of theimplemented solution by, for example, a machine learning module and/oran artificial intelligence module. If a particular implemented solutionis determined to be unsuccessful after a predetermined number ofimplementations (across one or more dental practices), the machinelearning module and/or artificial module may discontinue or remove thesolution from the pool of potential solutions. Conversely, if aparticular implemented solution is successful after a predeterminednumber of implementations, the machine learning module and/or artificialintelligence module can prioritize the solution over other potentialsolutions for the same issue. In such embodiments, the machine learningmodule and/or the artificial intelligence module can evaluateimplemented solutions for a number of different dental practices,including those sharing one or more characteristics or demographics, todetermine the suitability and priority of potential solutions for aparticular issue.

In various embodiments, method 1000 further comprises a step 1062 ofstoring trend data within the trend data base 111B. For example, thetrend data obtained in step 1060 and used to evaluate the solution canbe stored within trend database 111B for further analysis andutilization. Further, some or all of the trend data may be stored insystem database 111A.

With reference to FIG. 13, a process 1300 for managing content relevantto a dental practice in accordance with various embodiments isillustrated. Process 1300 may, for example, comprise a step 1370 ofcreating an article of content. In various embodiments, articles ofcontent can comprise information that is educational, instructive, orotherwise informative relating to aspects of the management of dentalpractices. For example, articles of content can comprise documents,videos, images, audio, or other content providing solutions to issuescommonly arising in the management of dental practices and/oradministration of dental care. In various embodiments, content createdin step 1370 may be stored, among other places, within content module118.

In various embodiments, process 1300 further comprises a step 1372 ofdetermining applicable tags for an article of content. For example, anarticle of content created in step 1370 can be evaluated to determineone or more applicable tags based upon the information contained in thearticle of content. With reference to FIGS. 13 and 14, an exemplary step1372 for determining appropriate tags for articles of content inaccordance with various embodiments is illustrated. The content may beingested and reviewed by content module 118 of DIP 108 to identify tagsassociated with the content. For example, content module 118 may usevoice recognition to detect the words present in an educational video.The words present in the video may be counted to generate a fingerprintof the most common terms based on the proportional use of the commonterms. The proportional use may be used to look up appropriate tags in alookup table. Additionally, content module 118 may accept user input toallow users to input desired tags associated with each article ofcontent.

In various embodiments, step 1372 comprises a sub-step 1480 ofdetermining an appropriate category of an applicable tag. For example,sub-step 1480 may comprise analyzing the information contained in thearticle of content to determine the appropriate category under which thearticle of content should be classified. In various embodiments, thecategory under which the article of content is classified is thebroadest aspect of the organizational structure of the tag. For example,appropriate categories may include data and process optimization,education, technology, and business, among others. After determining theappropriate category, the category is added as a part of the tag.

Step 1372 may further comprise a sub-step 1482 of determining anappropriate sub-category of an applicable tag. In various embodiments, atag may be classified under one or more sub-categories. For example, atag may be classified under one or two sub-categories. In variousembodiments, sub-categories may include clinical, financial,operational, sales, and platform sub-categories. After determining theappropriate sub-categories, the sub-categories are added as a part ofthe tag.

In various embodiments, step 1372 further comprises a step 1484 ofdetermining an appropriate component of an applicable tag. For example,a tag may be further classified by a component which corresponds to aspecific component of a DIP. Stated another way, the component underwhich the article of content is classified may comprise one or moremodules, components, or applications within a DIP, such as DIP 108 (ofFIG. 1A). In various embodiments, an appropriate component may compriseproduction, projected revenue, hygiene, patient base, messaging,accounts receivable, task manager, scheduling, and treatment planning,among others. After determining the appropriate components, thecomponents are added as a part of the tag.

Step 1372 may further comprise a sub-step 1486 of determining anappropriate issue of an applicable tag. In various embodiments, a tag isfurther classified (beyond a category, sub-category, and component) asrelating to one or more specific issues. For example, a tag may beclassified as relating to one or more issues including profit,production (dental hygiene production and/or doctor production), caseacceptance, schedule, human resources, policies and procedures, andcollections, among others. For example, sub-step 1486 comprisesevaluating the information contained in the article of content todetermine the appropriate issues under which a tag should be furtherclassified. After determining the appropriate issues, the issues areadded as a part of the tag.

In various embodiments, step 1372 comprises creating a tag matrix, intowhich the appropriate categories, sub-categories, components, and issuesare stored.

With reference back to FIG. 13, process 1300 can further comprise a step1374 of tagging the article of content with one or more appropriatetags. In various embodiments, step 1374 comprises applying the tag ortags determined in step 1372 to the article of content. For example, thearticle of content may comprise a footer, into which the tagging matrixof step 1372 is inserted. However, any manner of associating the tagwith the article of content is within the scope of the presentdisclosure.

In various embodiments, process 1300 comprises a step 1376 of verifyingtagging of an article of content. For example, an administrator orsystem user of the DIP can verify that the tag or tags generated andapplied by steps 1372 and 1374 were properly applied to the article ofcontent.

Process 1300 may further comprise, for example, a step 1378 of addingone or more content key words to the article of content. In variousembodiments, content key words can comprise single words or shortphrases which accurately describe one or more qualities of theinformation contained in the article of content.

In various embodiments, process 1300 further comprises a step 1380 ofstoring content in dental practice management system. For example, thearticle of content tagged in steps 1370-1378 may be stored within DIP108. In various embodiments, the article of content is stored withincontent module 118. In other embodiments, the article of content isstored within formatted database 111. Any manner of storing taggedarticles of content within DIP 108 is within the scope of the presentdisclosure.

With reference to FIGS. 1A and 15, a process 1500 for providing relevanttagged content to a dental practice in accordance with variousembodiments is illustrated. Process 1500 may, for example, comprise astep 1588 of identifying relevant tags. In various embodiments, step1588 comprises identifying one or more applicable tags within data, suchas first user data transmitted from first user system 102 to DIP 108.

For example, step 1588 may comprise the, by the content module,analyzing first user data to identify applicable tags. In variousembodiments, first user data is analyzed to determine the presence of apotential issue, problem, area of improvement, or other educationalopportunity which correspond to a category, sub-category, component,issue, or key words, such as those described in connection with process1300. The user data, which is derived from an individual dentalpractice, may be compared to a model of data derived from similar dentalpractices to identify shortcomings and/or areas for improvement. Forexample, if the comparison indicates that the individual dental practiceis converting a low rate of clients from the planning treatment phase tothe completed treatment phase, then the conversion rate may be an areaof deficiency. A lookup table containing tags associated with eachpotential deficiency may be stored in formatted database 111 and/orcontent module 118. DIP 108 may use the lookup table to identifyrelevant tags in response to the identified shortcoming.

In various embodiments, similar dental practices may include practiceshaving one or more characteristics (e.g., demographics) in common withthe dental practice utilizing first user system 102. For example,similar dental practices may comprise those operating in geographiclocations having similar population and/or economics, past performancemetric such as number of patients or annual revenue collected, or anyother characteristic that may be quantitatively compared to the dentalpractice of first user system 102.

In various embodiments, process 1500 further comprises a step 1590 ofselecting one or more appropriate articles of content based on tags. Forexample, step 1590 may comprise locating one or more articles ofcontent, stored in content module 118 and/or formatted database 111,which correspond to the tags identified in step 1588. In variousembodiments, step 1590 may also comprise selecting articles of contentwhich contain key words corresponding to the tags identified in step1588. For example, DIP 108 may select content from formatted database111 using a query using the identified tags and/or key words associatedwith the content as criteria for the query.

Process 1500 may further comprise, for example, a step 1592 ofdelivering the articles of content to a dental practice. For example,one or more articles of content identified in step 1590 may betransmitted by DIP 108 to first user system 102. In various embodiments,the articles of content are transmitted by application server 113 of DIP108. The articles of content may be displayed on a user interface alongwith quantitative and qualitative analysis relating to the dentalpractice. For example, an interaction point on an interface may bedisplayed along with a dashboard identifying a possible shortcoming andproposing educational content to improve the practitioner in theidentified areas.

In various embodiments, step 1592 can comprise a review of the articlesidentified in step 444 prior to transmitting the content to first usersystem 102. For example, a consultant utilizing consultant interface 109may review the content identified in step 1590 to determine if thecontent is relevant and potentially beneficial to the dental practiceutilizing first user system 102. Such review and approval may act as aquality assurance/quality control check on the content deliverymechanism.

In various embodiments, appropriate content can be selected byconsultant interface 109. For example, consultant interface 109 canidentify one or more issues based on analysis of first user datatransmitted from first user interface 115. In various embodiments, aconsultant utilizing consultant user system can search content module118 for content relating to the issue identified with the dentalpractice of first user system 102. For example, the consultant cansearch content module 118 using key words related to the issueidentified with the dental practice of first user interface 115. Afteridentifying appropriate content, the consultant utilizing consultantinterface 109 can instruct application server 113 to deliver the contentto first user interface 115.

DIP 108 may, for example, be configured to evaluate the effectiveness ofcontent provided to users, such as the dental practice of first usersystem 102. In various embodiments, DIP 108 comprises a correlationapplication running within content module 118 and/or data processingmodule 112. For example, the correlation application may evaluate aspecific criteria of a dental practice (e.g., revenue collection) afterthe delivery of content identified as relevant and potentiallybeneficial to the specific criteria. In various embodiments, thecorrelation application can determine if the specific criteria hasimproved, and by how much, over a specified time frame after delivery ofthe content. Further, the correlation application may, for example,compare the change in the specific criteria over the specified timeframe to a change in the same specific criteria over the same time framein one or more peer dental practices. Stated another way, thecorrelation application can evaluate if revenue collection improvedafter delivery of content related to improving revenue collection, forexample. In various embodiments, the improvement in the specificcriteria (such as revenue collection) may be recorded as a measure ofthe potential effectiveness of the content delivered to the dentalpractice.

Systems, methods and computer program products are provided. In thedetailed description herein, references to “various embodiments”, “oneembodiment”, “an embodiment”, “an example embodiment”, etc., indicatethat the embodiment described may include a particular feature,structure, or characteristic, but every embodiment may not necessarilyinclude the particular feature, structure, or characteristic. Moreover,such phrases are not necessarily referring to the same embodiment.Further, when a particular feature, structure, or characteristic isdescribed in connection with an embodiment, it is submitted that it iswithin the knowledge of one skilled in the art to affect such feature,structure, or characteristic in connection with other embodimentswhether or not explicitly described. After reading the description, itwill be apparent to one skilled in the relevant art(s) how to implementthe disclosure in alternative embodiments.

In various embodiments, the methods described herein are implementedusing the various particular machines described herein. The methodsdescribed herein may be implemented using the below particular machines,and those hereinafter developed, in any suitable combination, as wouldbe appreciated immediately by one skilled in the art. Further, as isunambiguous from this disclosure, the methods described herein mayresult in various transformations of certain articles.

The various system components discussed herein may include one or moreof the following: a host server or other computing systems including aprocessor for processing digital data; a memory coupled to the processorfor storing digital data; an input digitizer coupled to the processorfor inputting digital data; an application program stored in the memoryand accessible by the processor for directing processing of digital databy the processor; a display device coupled to the processor and memoryfor displaying information derived from digital data processed by theprocessor; and a plurality of databases. Various databases used hereinmay include: client data; merchant data; financial institution data;and/or like data useful in the operation of the system. As those skilledin the art will appreciate, user computer may include an operatingsystem (e.g., WINDOWS®, OS2, UNIX®, LINUX®, SOLARIS®, MacOS, etc.) aswell as various conventional support software and drivers typicallyassociated with computers.

The present system or any part(s) or function(s) thereof may beimplemented using hardware, software or a combination thereof and may beimplemented in one or more computer systems or other processing systems.However, the manipulations performed by embodiments were often referredto in terms, such as matching or selecting, which are commonlyassociated with mental operations performed by a human operator. No suchcapability of a human operator is necessary, or desirable in most cases,in any of the operations described herein. Rather, the operations may bemachine operations. Useful machines for performing the variousembodiments include general purpose digital computers or similardevices.

In fact, in various embodiments, the embodiments are directed toward oneor more computer systems capable of carrying out the functionalitydescribed herein. The computer system includes one or more processors,such as processor. The processor is connected to a communicationinfrastructure (e.g., a communications bus, cross over bar, or network).Various software embodiments are described in terms of this exemplarycomputer system. After reading this description, it will become apparentto a person skilled in the relevant art(s) how to implement variousembodiments using other computer systems and/or architectures. Computersystem can include a display interface that forwards graphics, text, andother data from the communication infrastructure (or from a frame buffernot shown) for display on a display unit.

The computer system also includes a main memory, such as for examplerandom access memory (RAM), and may also include a secondary memory. Thesecondary memory may include, for example, a hard disk drive and/or aremovable storage drive, representing a floppy disk drive, a magnetictape drive, an optical disk drive, etc. The removable storage drivereads from and/or writes to a removable storage unit in a well-knownmanner. Removable storage unit represents a floppy disk, magnetic tape,optical disk, etc. which is read by and written to by removable storagedrive. As will be appreciated, the removable storage unit includes acomputer usable storage medium having stored therein computer softwareand/or data.

In various embodiments, secondary memory may include other similardevices for allowing computer programs or other instructions to beloaded into computer system. Such devices may include, for example, aremovable storage unit and an interface. Examples of such may include aprogram cartridge and cartridge interface (such as that found in videogame devices), a removable memory chip (such as an erasable programmableread only memory (EPROM), or programmable read only memory (PROM)) andassociated socket, and other removable storage units and interfaces,which allow software and data to be transferred from the removablestorage unit to computer system.

The computer system may also include a communications interface.Communications interface allows software and data to be transferredbetween computer system and external devices. Examples of communicationsinterface may include a modem, a network interface (such as an Ethernetcard), a communications port, a Personal Computer Memory CardInternational Association (PCMCIA) slot and card, etc. Software and datatransferred via communications interface are in the form of signalswhich may be electronic, electromagnetic, and optical or other signalscapable of being received by communications interface. These signals areprovided to communications interface via a communications path (e.g.,channel). This channel carries signals and may be implemented usingwire, cable, fiber optics, a telephone line, a cellular link, a radiofrequency (RF) link, wireless and other communications channels.

The terms “computer program medium” and “computer usable medium” and“computer readable medium” are used to generally refer to media such asremovable storage drive and a hard disk installed in hard disk drive.These computer program products provide software to computer system.

Computer programs (also referred to as computer control logic) arestored in main memory and/or secondary memory. Computer programs mayalso be received via communications interface. Such computer programs,when executed, enable the computer system to perform the features asdiscussed herein. In particular, the computer programs, when executed,enable the processor to perform the features of various embodiments.Accordingly, such computer programs represent controllers of thecomputer system.

In various embodiments, software may be stored in a computer programproduct and loaded into computer system using removable storage drive,hard disk drive or communications interface. The control logic(software), when executed by the processor, causes the processor toperform the functions of various embodiments as described herein. Invarious embodiments, hardware components such as application specificintegrated circuits (ASICs). Implementation of the hardware statemachine so as to perform the functions described herein will be apparentto persons skilled in the relevant art(s).

A web client may be installed on the various computing devices describedherein, which may include any device (e.g., personal computer) whichcommunicates via any network, for example such as those discussedherein. Such browser applications comprise Internet browsing softwareinstalled within a computing unit or a system to conduct onlinetransactions and/or communications. These computing units or systems maytake the form of a computer or set of computers, although other types ofcomputing units or systems may be used, including laptops, notebooks,tablets, hand held computers, personal digital assistants, set-topboxes, workstations, computer-servers, main frame computers,mini-computers, PC servers, pervasive computers, network sets ofcomputers, personal computers, such as IPADS®, IMACS®, and MACBOOKS®,kiosks, terminals, point of sale (POS) devices and/or terminals,televisions, or any other device capable of receiving data over anetwork. A web-client may run MICROSOFT® INTERNET EXPLORER®, MOZILLA®FIREFOX®, GOOGLE® CHROME®, APPLE® Safari, or any other of the myriadsoftware packages available for browsing the internet.

Practitioners will appreciate that a web client may or may not be indirect contact with an application server. For example, a web client mayaccess the services of an application server through another serverand/or hardware component, which may have a direct or indirectconnection to an Internet server. For example, a web client maycommunicate with an application server via a load balancer. In variousembodiments, access is through a network or the Internet through acommercially-available web-browser software package.

As those skilled in the art will appreciate, a web client includes anoperating system (e.g., WINDOWS®/CE/Mobile, OS2, UNIX®, LINUX®,SOLARIS®, MacOS, etc.) as well as various conventional support softwareand drivers typically associated with computers. A web client mayinclude any suitable personal computer, network computer, workstation,personal digital assistant, cellular phone, smart phone, minicomputer,mainframe or the like. A web client can be in a home or businessenvironment with access to a network. In various embodiments, access isthrough a network or the Internet through a commercially availableweb-browser software package. A web client may implement securityprotocols such as Secure Sockets Layer (SSL) and Transport LayerSecurity (TLS). A web client may implement several application layerprotocols including http, https, ftp, and sftp.

Any of the communications, inputs, storage, databases or displaysdiscussed herein may be facilitated through a website having web pages.The term “web page” as it is used herein is not meant to limit the typeof documents and applications that might be used to interact with theuser. For example, a typical website might include, in addition tostandard HTML documents, various forms, JAVA® APPLE®ts, JAVASCRIPT,active server pages (ASP), common gateway interface scripts (CGI),extensible markup language (XML), dynamic HTML, cascading style sheets(CSS), AJAX (Asynchronous JAVASCRIPT And XML), helper applications,plug-ins, and the like. A server may include a web service that receivesa request from a web server, the request including a URL and an IPaddress (123.56.192.234). The web server retrieves the appropriate webpages and sends the data or applications for the web pages to the IPaddress. Web services are applications that are capable of interactingwith other applications over a communications means, such as theinternet. Web services are typically based on standards or protocolssuch as XML, SOAP, AJAX, WSDL and UDDI. Web services methods are wellknown in the art, and are covered in many standard texts. See, e.g.,Alex Nghiem, IT Web Services: A Roadmap for the Enterprise (2003),hereby incorporated by reference.

Practitioners will also appreciate that there are a number of methodsfor displaying data within a browser-based document. Data may berepresented as standard text or within a fixed list, scrollable list,drop-down list, editable text field, fixed text field, pop-up window,and the like. Likewise, there are a number of methods available formodifying data in a web page such as, for example, free text entry usinga keyboard, selection of menu items, check boxes, option boxes, and thelike.

“Cloud” or “Cloud computing” includes a model for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, servers, storage, applications, and services)that can be rapidly provisioned and released with minimal managementeffort or service provider interaction. Cloud computing may includelocation-independent computing, whereby shared servers provideresources, software, and data to computers and other devices on demand.For more information regarding cloud computing, see the NIST's (NationalInstitute of Standards and Technology) definition of cloud computing athttp://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf (lastvisited June 2012), which is hereby incorporated by reference in itsentirety.

As used herein, “transmit” may include sending electronic data from onesystem component to another over a network connection. Additionally, asused herein, “data” may include encompassing information such ascommands, queries, files, data for storage, and the like in digital orany other form.

The system and method may be described herein in terms of functionalblock components, screen shots, optional selections and variousprocessing steps. It should be appreciated that such functional blocksmay be realized by any number of hardware and/or software componentsconfigured to perform the specified functions. For example, the systemmay employ various integrated circuit components, e.g., memory elements,processing elements, logic elements, look-up tables, and the like, whichmay carry out a variety of functions under the control of one or moremicroprocessors or other control devices. Similarly, the softwareelements of the system may be implemented with any programming orscripting language such as C, C++, C#, JAVA®, JAVASCRIPT, VBScript,Macromedia Cold Fusion, COBOL, MICROSOFT® Active Server Pages, assembly,PERL, PHP, awk, Python, Visual Basic, SQL Stored Procedures, PL/SQL, anyUNIX shell script, and extensible markup language (XML) with the variousalgorithms being implemented with any combination of data structures,objects, processes, routines or other programming elements. Further, itshould be noted that the system may employ any number of conventionaltechniques for data transmission, signaling, data processing, networkcontrol, and the like. Still further, the system could be used to detector prevent security issues with a client-side scripting language, suchas JAVASCRIPT, VBScript or the like. For a basic introduction ofcryptography and network security, see any of the following references:(1) “Applied Cryptography: Protocols, Algorithms, And Source Code In C,”by Bruce Schneier, published by John Wiley & Sons (second edition,1995); (2) “JAVA® Cryptography” by Jonathan Knudson, published byO'Reilly & Associates (1998); (3) “Cryptography & Network Security:Principles & Practice” by William Stallings, published by Prentice Hall;all of which are hereby incorporated by reference.

The term “non-transitory” is to be understood to remove only propagatingtransitory signals per se from the claim scope and does not relinquishrights to all standard computer-readable media that are not onlypropagating transitory signals per se. Stated another way, the meaningof the term “non-transitory computer-readable medium” and“non-transitory computer-readable storage medium” should be construed toexclude only those types of transitory computer-readable media whichwere found in In Re Nuijten to fall outside the scope of patentablesubject matter under 35 U.S.C. § 101.

Benefits, other advantages, and solutions to problems have beendescribed herein with regard to specific embodiments. However, thebenefits, advantages, solutions to problems, and any elements that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as critical, required, or essentialfeatures or elements of the disclosure. The scope of the disclosure isaccordingly to be limited by nothing other than the appended claims, inwhich reference to an element in the singular is not intended to mean“one and only one” unless explicitly so stated, but rather “one ormore.” Moreover, where a phrase similar to ‘at least one of A, B, and C’or ‘at least one of A, B, or C’ is used in the claims or specification,it is intended that the phrase be interpreted to mean that A alone maybe present in an embodiment, B alone may be present in an embodiment, Calone may be present in an embodiment, or that any combination of theelements A, B and C may be present in a single embodiment; for example,A and B, A and C, B and C, or A and B and C.

Although the disclosure includes a method, it is contemplated that itmay be embodied as computer program instructions on a tangiblecomputer-readable carrier, such as a magnetic or optical memory or amagnetic or optical disk. All structural and/or functional equivalentsto the elements of the above-described various embodiments that areknown to those of ordinary skill in the art are expressly incorporatedherein by reference and are intended to be encompassed by the presentclaims. Moreover, it is not necessary for a device or method to addresseach and every problem sought to be solved by the present disclosure,for it to be encompassed by the present claims. Furthermore, no element,component, or method step in the present disclosure is intended to bededicated to the public regardless of whether the element, component, ormethod step is explicitly recited in the claims. No claim element isintended to invoke 35 U.S.C. 112(f) unless the element is expresslyrecited using the phrase “means for.” As used herein, the terms“comprises”, “comprising”, or any other variation thereof, are intendedto cover a non-exclusive inclusion, such that a process, method,article, or apparatus that comprises a list of elements does not includeonly those elements but may include other elements not expressly listedor inherent to such process, method, article, or apparatus.

Embodiments

A method comprising: creating an article of content relevant to a dentalpractice; determining at least one tag for the article of content;tagging the article of content with the at least one tag; verifying thetagging of the article of content; adding at least one key word relatedto the at least one tag to the article of content; and storing thearticle of content in a dental integration platform (DIP).

The above-method further comprising identifying a shortcoming of thedental practice by comparing the dental practice to similar dentalpractices; and transmitting, by the DIP, the article of content to thedental practice in response to identifying the shortcoming.

The above-method, wherein the DIP comprises an application configured toreceive a first user data and identify an applicable tag within thefirst user data. The above-method, wherein the application is executedby a content module.

The above-method, wherein the step of determining at least one tag forthe article of content comprises determining an appropriate category ofthe at least one tag; determining an appropriate sub-category within theappropriate category of the at least one tag; determining an appropriatecomponent of the at least one tag; and determining an appropriate issueof the at least one tag.

The above-method, wherein the article of content is stored within thecontent module.

A computer-based system, comprising: a first user system incommunication with a dental integration platform (DIP), the DIPcomprising a database and a content module, wherein the first usersystem associated with a dental practice is configured to transmit afirst user data to the DIP, wherein the first user data is stored in thedatabase, wherein the content module comprises a processor and atangible, non-transitory memory configured to communicate with theprocessor and having instructions stored thereon, the content moduleconfigured, upon execution of the instructions by the processor, to:identify at least one of an applicable tag and an applicable key wordfrom the first user data stored in the database; identify an article ofcontent comprising at least one of the applicable tag and the applicablekey word; and transmit the article of content to a first user interface.

The above-system, further comprising a consultant interface incommunication with the DIP and configured to instruct the DIP totransmit the article of content to the first user interface.

The above-system, further comprising a data transmitting moduleconfigured to receive data from the first user system.

The above-system, wherein the content module is further configured todetermine an appropriate category of the tag; determine an appropriatesub-category within the appropriate category of the tag; determine anappropriate component of the tag; and determine an appropriate issue ofthe tag.

The above-system, wherein the article of content is stored within thecontent module.

An article of manufacture including a non-transitory, tangible computerreadable storage medium having instructions stored thereon that, inresponse to execution by a computer-based system, cause a content moduleof a dental practice management system (DIP) to perform operationscomprising: determining at least one tag for an article of contentstored within the DIP; tagging the article of content with the at leastone tag; verifying the tagging of the article of content; and adding atleast one key word related to the at least one tag to the article ofcontent.

The above-article of manufacture, wherein the content module is furtherconfigured to transmit the article of content to a dental practice inresponse to identifying a shortcoming of the dental practice.

The above-article of manufacture, wherein the content module is furtherconfigured to receive a first user data and identify an applicable tagwithin the first user data.

The above-article of manufacture, wherein determining at least one tagfor the article of content comprises: determining an appropriatecategory of the tag; determining an appropriate sub-category within theappropriate category of the tag; determining an appropriate component ofthe tag; and determining an appropriate issue of the tag.

The above-article, wherein the article of content is stored within thecontent module.

What is claimed is:
 1. A method comprising: receiving, by a processor, afirst user data from a first user system associated with a dentalpractice; converting, by the processor using a data transmitting module,the first user data in a first format to a second common format with aplurality of dental practices, by mapping fields of the first user datainto a schema that supports the second common format; processing, by theprocessor, the first user data to create dental treatment datacomprising a dental treatment plan with dental service codes for eachpatient of the first user data, wherein the dental treatment planincludes dental hygiene procedures, recommended dental treatments anddates for scheduling the recommended dental treatments; determining, bythe processor, scheduling efficiency data by comparing potential revenuefrom the dental hygiene procedures and the recommended dental treatmentswith total dental treatments accepted, total dental treatmentsscheduled, total dental treatments completed and total dental treatmentsperformed; creating, by the processor, scheduling data comprising adaily schedule of dental treatments to be performed by each employee ofthe dental practice; comparing, by the processor, the scheduling data ofthe dental practice with scheduling data of a plurality of dentalpractices sharing one or more characteristics with the dental practice;creating, by the processor, suggestions for improvement in practicemanagement and practical skills involving hygiene based on the comparingof the scheduling data; formatting, by the processor using anapplication server, the dental treatment data and scheduling efficiencydata for transmittal to a first user interface; creating, by theprocessor, a schedule model based on the dental treatment data of aplurality of dental practices sharing one or more characteristics withthe dental practice; comparing, by the processor, the dental treatmentdata and the scheduling efficiency data with the schedule model;filtering, by the processor, patient and financial data from the firstuser data; generating, by the processor, financial projections for thedental practice based on financial factors and the patient and financialdata; generating, by the processor, a financial model from the patientand financial data and the financial projections based on the pluralityof dental practices in a local geographic area; selecting, by theprocessor, and based on the schedule model and the financial model, anoperational issue from an issue database using the quantifiable metricto identify the operational issue, wherein the operational issuecomprises an issue profile, wherein the issue profile comprises thequantifiable metric in response to the quantifiable metric being below athreshold value; tagging, by the processor, an article of contentrelated to the operational issue, wherein the article of contentincludes dental clinical content including hygiene; adding, by theprocessor, a content key word to the article of content; identifying, bythe processor, a solution corresponding with the issue profile, whereinthe solution comprises the article of content; confirming, by theprocessor, the solution; receiving, by the processor, an indication thatthe confirmed solution is implemented; evaluating, by the processorusing a machine learning module, an effectiveness of the confirmedsolution by analyzing trend data for the quantifiable metric for aperiod after the confirmed solution is implemented in a plurality ofdental practices sharing one or more characteristics with the dentalpractice; and modifying, by the processor, the solution based on thetrend data from evaluating the effectiveness of the confirmed solution.2. The method of claim 1, wherein the confirming the solution comprisestransmitting, by a dental integration platform (DIP), the solution to aconsultant user interface and receiving, from the consultant userinterface, a confirmation from a consultant for the solution.
 3. Themethod of claim 1, wherein the confirming the solution comprises, by atleast one of a machine learning module or an artificial intelligencemodule, instructing the first user system to implement the solution. 4.The method of claim 1, wherein the quantifiable metric comprises atleast one of a projected financial data, an acceptance rate data, acompletion rate data, a potential revenue of planned to accepted dentaltreatments data, a percentage revenue of accepted to scheduled dentaltreatments data, a potential revenue of scheduled to completed dentaltreatments data, and a percentage revenue of accepted to completeddental treatments data.
 5. The method of claim 1, wherein the financialprojections comprise a projected dental treatment revenue, a projectedaccepted revenue, a projected completed revenue, and expense data for apredetermined time period.
 6. The method of claim 1, wherein thefinancial model comprises an average annual potential revenue, anaverage annual accepted revenue, an average completed revenue, expensedata, an average T_(PA), an average T_(AS), an average T_(SC), and anaverage T_(PC) of the plurality of dental practices.
 7. The method ofclaim 1, further comprising determining, by the processor via theconsultant user interface, a subset of data that is transmitted to thefirst user interface.
 8. The method of claim 1, wherein the financialfactors are generated from potential revenue of the planned dentaltreatment to the accepted dental treatment ($R_(PA)), a percentagerevenue of the planned dental treatment to the accepted dental treatment(% R_(PA)), a potential revenue of the accepted dental treatment to thescheduled dental treatment ($R_(AS)), a potential revenue of thescheduled dental treatment to the completed dental treatment ($R_(SC)),and a percentage revenue of the accepted dental treatment to thecompleted dental treatment (% R_(AC)) .
 9. The method of claim 1,further comprising storing, by the processor, the first user data in atleast one of a relational database comprising various tables related bykeys, a non-relational database or a hybrid database.
 10. The method ofclaim 1, wherein the financial model comprises an average of an actualrevenue collected of each of the plurality of dental practices havingthe predetermined characteristics.
 11. The method of claim 1, whereinthe schedule model comprises at least one of an average time ofaccepting a dental treatment and an average time of completing a dentaltreatment of each of the plurality of dental practices having thepredetermined characteristics.
 12. The method of claim 1, wherein thesolution comprises at least one of a document, video, image or audio.13. The method of claim 1, wherein the trend data is stored within atrend database of a dental integration platform (DIP).
 14. The method ofclaim 1, wherein the trend data is captured at an interval of at leastone of 30 days, 60 days, 90 days, or 120 days.
 15. The method of claim1, wherein the solution is communicated to a first user via the firstuser interface.
 16. The method of claim 1, wherein the scheduling modelcomprises comprising an average time period from a planned dentaltreatment to an accepted dental treatment (T_(PA)), an average timeperiod from the accepted dental treatment to a scheduled dentaltreatment (T_(AS)), an average time period from the scheduled dentaltreatment to a completed dental treatment (T_(SC)), and an average timeperiod from the planned dental treatment to the completed dentaltreatment (T_(PC)) .
 17. The method of claim 1, further comprisinginstructing a dental integration platform (DIP) to transmit thefinancial projections and the scheduling data to the first userinterface.
 18. The method of claim 1, further comprising transmitting,by the processor using an application server, at least one of the dentaltreatment data, financial projections, scheduling efficiency data,scheduling data, suggestions for improvement, financial projections orsolution to the first user interface.
 19. An article of manufactureincluding a non-transitory, tangible computer readable storage mediumhaving instructions stored thereon that, in response to execution by acomputer-based system, cause the computer-based system to performoperations comprising: receiving, by the processor, a first user datafrom a first user system associated with a dental practice; converting,by the processor using a data transmitting module, the first user datain a first format to a second common format with a plurality of dentalpractices, by mapping fields of the first user data into a schema thatsupports the second common format; processing, by the processor, thefirst user data to create dental treatment data comprising a dentaltreatment plan with dental service codes for each patient of the firstuser data, wherein the dental treatment plan includes dental hygieneprocedures, recommended dental treatments and dates for scheduling therecommended dental treatments; determining, by the processor, schedulingefficiency data by comparing potential revenue from the dental hygieneprocedures and the recommended dental treatments with total dentaltreatments accepted, total dental treatments scheduled, total dentaltreatments completed and total dental treatments performed; creating, bythe processor, scheduling data comprising a daily schedule of dentaltreatments to be performed by each employee of the dental practice;comparing, by the processor, the scheduling data of the dental practicewith scheduling data of a plurality of dental practices sharing one ormore characteristics with the dental practice; creating, by theprocessor, suggestions for improvement in practice management andpractical skills involving hygiene based on the comparing of thescheduling data; formatting, by the processor using an applicationserver, the dental treatment data and scheduling efficiency data fortransmittal to a first user interface; creating, by the processor, aschedule model based on the dental treatment data of a plurality ofdental practices sharing one or more characteristics with the dentalpractice; comparing, by the processor, the dental treatment data and thescheduling efficiency data with the schedule model; filtering, by theprocessor, patient and financial data from the first user data;generating, by the processor, financial projections for the dentalpractice based on financial factors and the patient and financial data;generating, by the processor, a financial model from the patient andfinancial data and the financial projections based on the plurality ofdental practices in a local geographic area; selecting, by theprocessor, and based on the schedule model and the financial model, anoperational issue from an issue database using the quantifiable metricto identify the operational issue, wherein the operational issuecomprises an issue profile, wherein the issue profile comprises thequantifiable metric in response to the quantifiable metric being below athreshold value; tagging, by the processor, an article of contentrelated to the operational issue, wherein the article of contentincludes dental clinical content including hygiene; adding, by theprocessor, a content key word to the article of content; identifying, bythe processor, a solution corresponding with the issue profile, whereinthe solution comprises the article of content; confirming, by theprocessor, the solution; receiving, by the processor, an indication thatthe confirmed solution is implemented; evaluating, by the processorusing a machine learning module, an effectiveness of the confirmedsolution by analyzing trend data for the quantifiable metric for aperiod after the confirmed solution is implemented in a plurality ofdental practices sharing one or more characteristics with the dentalpractice; and modifying, by the processor, the solution based on thetrend data from evaluating the effectiveness of the confirmed solution.20. A system comprising: a processor; and a tangible, non-transitorymemory configured to communicate with the processor, the tangible,non-transitory memory having instructions stored thereon that, inresponse to execution by the processor, cause the processor to performoperations comprising: receiving, by the processor, a first user datafrom a first user system associated with a dental practice; converting,by the processor using a data transmitting module, the first user datain a first format to a second common format with a plurality of dentalpractices, by mapping fields of the first user data into a schema thatsupports the second common format; processing, by the processor, thefirst user data to create dental treatment data comprising a dentaltreatment plan with dental service codes for each patient of the firstuser data, wherein the dental treatment plan includes dental hygieneprocedures, recommended dental treatments and dates for scheduling therecommended dental treatments; determining, by the processor, schedulingefficiency data by comparing potential revenue from the dental hygieneprocedures and the recommended dental treatments with total dentaltreatments accepted, total dental treatments scheduled, total dentaltreatments completed and total dental treatments performed; creating, bythe processor, scheduling data comprising a daily schedule of dentaltreatments to be performed by each employee of the dental practice;comparing, by the processor, the scheduling data of the dental practicewith scheduling data of a plurality of dental practices sharing one ormore characteristics with the dental practice; creating, by theprocessor, suggestions for improvement in practice management andpractical skills involving hygiene based on the comparing of thescheduling data; formatting, by the processor using an applicationserver, the dental treatment data and scheduling efficiency data fortransmittal to a first user interface; creating, by the processor, aschedule model based on the dental treatment data of a plurality ofdental practices sharing one or more characteristics with the dentalpractice; comparing, by the processor, the dental treatment data and thescheduling efficiency data with the schedule model; filtering, by theprocessor, patient and financial data from the first user data;generating, by the processor, financial projections for the dentalpractice based on financial factors and the patient and financial data;generating, by the processor, a financial model from the patient andfinancial data and the financial projections based on the plurality ofdental practices in a local geographic area; selecting, by theprocessor, and based on the schedule model and the financial model, anoperational issue from an issue database using the quantifiable metricto identify the operational issue, wherein the operational issuecomprises an issue profile, wherein the issue profile comprises thequantifiable metric in response to the quantifiable metric being below athreshold value; tagging, by the processor, an article of contentrelated to the operational issue, wherein the article of contentincludes dental clinical content including hygiene; adding, by theprocessor, a content key word to the article of content; identifying, bythe processor, a solution corresponding with the issue profile, whereinthe solution comprises the article of content; confirming, by theprocessor, the solution; receiving, by the processor, an indication thatthe confirmed solution is implemented; evaluating, by the processorusing a machine learning module, an effectiveness of the confirmedsolution by analyzing trend data for the quantifiable metric for aperiod after the confirmed solution is implemented in a plurality ofdental practices sharing one or more characteristics with the dentalpractice; and modifying, by the processor, the solution based on thetrend data from evaluating the effectiveness of the confirmed solution.